Johanson, ArneHasselbring, WilhelmBecker, SteffenBogicevic, IvanHerzwurm, GeorgWagner, Stefan2019-03-142019-03-142019978-3-88579-686-2https://dl.gi.de/handle/20.500.12116/20924Despite the increasing importance of in silico experiments to the scientific discovery process, state-of-the-art software engineering practices are rarely adopted in computational science. To understand the underlying causes for this situation and to identify ways to improve it, we conducted a literature survey on software engineering practices in computational science. We identified recurring key characteristics of scientific software development that are the result of the nature of scientific challenges, the limitations of computers, and the cultural environment of scientific software development. Our findings allow us to point out shortcomings of existing approaches for bridging the gap between software engineering and computational science and to provide an outlook on promising research directions that could contribute to improving the current situation.enComputational ScienceModel-driven software engineeringSoftware architectureText/Conference Paper10.18420/se2019-081617-5468